Network inference and the analysis of a sub-network involved in the toxicological response are described in this chapter. The chapter introduces the project and the scientific context in which it was conceived and reviews the materials and methods used in the experiment. The methods section is organized into three parts that describe the data gathering process and inference of a gene network, the use of two network visualization tools (Cytoscape and NetView), and the analysis of a gene whose dysfunction implies a toxic response. The data gathering process consists of the selection of genome-wide gene expression profiles from public repositories and a subsequent data-formatting step. This part includes all necessary instructions indicating how to install and run the inference algorithm to generate a gene network from the data retrieved in the previous step. The second part of the section overviews the two network visualization tools used in the experiment, Cytoscape and NetView. Cytoscape was loaded with a mock gene network whose source files for its inference are distributed with the chapter. Alternately, NetView is pre-loaded, as it serves as a web interface to access mammalian gene networks. Lastly, this section describes how information of interest is extracted from the human NetView gene network. The chapter presents the findings of a study case, during which the gene of interest, the copper (Cu)-transporting ATPase gene ATP7A, is investigated. Mutations in ATP7A lead to the toxic accumulation of Cu in the intestinal epithelium and deficit of the metal in other tissues, thus causing Menkes disease. By identifying a network of genes that co-express with ATP7A, we identified targets that may disrupt trafficking of the protein product of the gene, which thus influence the toxicological outcomes of the disease. The last part of the chapter assesses a biological validation of NetView predictions, and provides wet lab protocols that may be used to identify the molecular players involved in ATP7A trafficking.
Toxicological assessment via gene network analysis
Gregoretti Francesco;Oliva Gennaro;
2015
Abstract
Network inference and the analysis of a sub-network involved in the toxicological response are described in this chapter. The chapter introduces the project and the scientific context in which it was conceived and reviews the materials and methods used in the experiment. The methods section is organized into three parts that describe the data gathering process and inference of a gene network, the use of two network visualization tools (Cytoscape and NetView), and the analysis of a gene whose dysfunction implies a toxic response. The data gathering process consists of the selection of genome-wide gene expression profiles from public repositories and a subsequent data-formatting step. This part includes all necessary instructions indicating how to install and run the inference algorithm to generate a gene network from the data retrieved in the previous step. The second part of the section overviews the two network visualization tools used in the experiment, Cytoscape and NetView. Cytoscape was loaded with a mock gene network whose source files for its inference are distributed with the chapter. Alternately, NetView is pre-loaded, as it serves as a web interface to access mammalian gene networks. Lastly, this section describes how information of interest is extracted from the human NetView gene network. The chapter presents the findings of a study case, during which the gene of interest, the copper (Cu)-transporting ATPase gene ATP7A, is investigated. Mutations in ATP7A lead to the toxic accumulation of Cu in the intestinal epithelium and deficit of the metal in other tissues, thus causing Menkes disease. By identifying a network of genes that co-express with ATP7A, we identified targets that may disrupt trafficking of the protein product of the gene, which thus influence the toxicological outcomes of the disease. The last part of the chapter assesses a biological validation of NetView predictions, and provides wet lab protocols that may be used to identify the molecular players involved in ATP7A trafficking.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.